By Mark Watts
The radiologist’s note came through quietly. He had accepted the invitation to meet the following Wednesday. It caught me off guard. I was grateful, certainly, but also surprised.
He had just moved to Canada after 32 years practicing in the United States, stepping into a different system at a moment in his career when most physicians begin to slow down. Not long before that, he had been featured in a HIMSS video discussing two subjects that have shaped much of my own thinking: imaging and innovation.
At one point in that interview, he was asked a deceptively simple question. What is the difference between the American and Canadian healthcare systems? His answer was just two words.
“Culture and ownership.”
It is the kind of response that feels incomplete at first, and then steadily expands the more you sit with it.
Over the past several days, moving through different healthcare environments across the United States, I have found myself returning to that answer. On the surface, the conversations sound the same everywhere you go. Every hospital, health system and clinic seems to speak the same language now. Artificial intelligence. Imaging. Digital infrastructure. Staffing shortages. Operational strain. The complexity of modern medicine. Implementation.
It would be easy, listening to these conversations, to believe that the system is moving in a shared direction, that there is a coherent, unified arc toward the future of care.
That impression does not last very long.
Spend time inside the institutions themselves, walk the floors, listen carefully, sit in on meetings that do not show up in presentations and a different reality emerges. The future does not arrive evenly. It does not even arrive predictably. In some places, transformation is real and visible. In others, it is aspirational. In many, it sits somewhere in between, promising in theory but uneven in practice.
These differences are not primarily about access to technology. Most organizations can point to some form of artificial intelligence initiative, some degree of imaging modernization, some kind of digital roadmap. The divergence shows up elsewhere.
It appears in how decisions are made. In who carries responsibility when something goes wrong. In how risk is understood, tolerated or avoided. In the degree to which clinicians trust new systems entering their workflows. In whether leadership sees innovation as a necessity or as something to be cautiously tested and contained.
These are not technical distinctions. They are cultural ones.
Culture shapes outcomes more powerfully than most people expect.
This helps explain why healthcare continues to resist simple, clean narratives about innovation. In other sectors, technological progress often follows a more recognizable pattern. A new capability emerges, adoption grows and eventually the old way fades. The path is rarely smooth, but it is visible.
Healthcare does not behave that way.
Technology enters a system already dense with tradition, professional identity, regulation and deeply ingrained habits. It meets clinicians whose judgment has been formed over decades, administrators balancing competing pressures and patients whose experiences are filtered through trust and access. Nothing enters a blank environment.
For that reason, progress tends to fragment. A system that works well in one institution struggles to take hold in another. A tool that performs convincingly in controlled settings encounters hesitation in day-to-day practice. Something designed to reduce burden can unintentionally add complexity when deployed at scale.
None of this is especially surprising once you begin to see it clearly.
The deeper insight comes from stepping outside formal narratives and listening to quieter conversations, the ones that happen between people who have spent years inside medicine. These conversations are not designed for conferences or investor briefings. They are candid, sometimes uncertain and often more grounded.
Within those exchanges, a different map begins to take shape. You start to hear where something truly improved care, where it struggled despite strong expectations, and where the gap between what is possible and what is achievable remains larger than expected.
That gap matters.
It is shaped less by the inherent value of the innovation and more by the environment into which it is introduced.
This is where the radiologist’s observation about culture and ownership becomes more precise. Different countries operate from different assumptions about who the system serves, who holds responsibility for outcomes and how decisions should be made. Those assumptions are not abstract. They influence procurement, clinical adoption, governance and the willingness to change.
In systems where ownership is centralized or broadly shared, decisions can move with coordination, but sometimes at the cost of speed or flexibility. In systems where ownership is distributed, there may be more local autonomy, but also more variability. Neither model is inherently better. Each reflects the values that shape it.
What becomes clear is that innovation does not stand apart from that context. It is carried by it.
A technology is not simply judged on capability. It is absorbed or resisted through the lens of local expectations, institutional norms and accountability structures. The same solution can perform very differently depending on where it lands.
This is particularly visible in medical imaging, where technical progress continues to accelerate. Artificial intelligence offers the promise of faster interpretation, improved detection and more efficient workflows. In some environments, those gains are materializing in meaningful ways.
In others, the same tools encounter friction. Questions around responsibility and liability remain unresolved. Integration into existing workflows proves more complicated than expected. Clinicians approach cautiously, not because they reject the technology outright, but because the surrounding system has not adapted to support it.
The result is not a simple failure of the innovation. It is a misalignment between what the technology assumes and what the environment can sustain. The longer you spend in healthcare, the more difficult it becomes to separate those two elements.
Innovation is often described as if it exists independently, something that can be evaluated, funded and then scaled. In practice, it is deeply dependent on alignment across culture, leadership, incentives and everyday operations. That alignment is difficult to create and even more difficult to maintain.
Which brings the focus back to implementation.
For years, implementation was seen as the final stage of innovation, the point at which something already validated would be deployed. It was treated as a downstream activity, something that followed the real work. That framing no longer reflects reality.
Implementation has become the defining challenge, not because ideas are lacking, but because making those ideas function within real systems requires navigating the complexity of those systems. It involves culture, trust, workflow and sometimes revisiting the design of the innovation itself.
Implementation is not where innovation ends. It is where it is tested.
And that test plays out differently depending on where it occurs.
Different countries, different health systems and even different institutions within the same region each carry their own understanding of how healthcare should function and who is responsible for making it work.
Technology enters that landscape as a possibility. What it becomes depends on whether the environment can carry it forward.
That is not always the most visible part of innovation. But it is the part that ultimately determines what changes and what does not.
Mark Watts is an experienced imaging professional who founded an AI company called Zenlike.ai.
